{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\HuangSX\\AppData\\Roaming\\Python\\Python37\\site-packages\\tensorflow\\python\\compat\\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "non-resource variables are not supported in the long term\n"
     ]
    }
   ],
   "source": [
    "# 声明库\n",
    "import numpy as np\n",
    "import tensorflow.compat.v1 as tf\n",
    "tf.disable_v2_behavior()\n",
    "from matplotlib import pyplot as plt\n",
    "from PIL import Image\n",
    "\n",
    "%matplotlib inline\n",
    "assert tf.__version__ >= '1.4.0', 'Please upgrade your tensorflow installation to v1.4.* or later!'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(194, 259, 3) uint8\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 测试图片读取\n",
    "img = Image.open(r'C:/Users/HuangSX/Desktop/OpenCV/data/HappyFish.jpg')\n",
    "img = np.asarray(img, dtype=np.uint8)\n",
    "plt.imshow(img)\n",
    "print(img.shape,img.dtype)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "195.43942469715665\n",
      "0.7664291164594379\n",
      "(1, 194, 259, 3)\n"
     ]
    }
   ],
   "source": [
    "# 输出图片像素的原始均值\n",
    "print(img.mean())\n",
    "# 图片像素归一化处理\n",
    "img = img/255\n",
    "print(img.mean())\n",
    "# 3d 转换成 4d(axiass=0,即:在切片0位置插入1个维度)\n",
    "if len(img.shape) != 4:\n",
    "    img = np.expand_dims(img, axis=0)\n",
    "    \n",
    "print(img.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 输入图像补0处理\n",
    "def picPad0(input, filter, stride, outShape):    \n",
    "    \"\"\"\n",
    "        padding='same'的补0处理逻辑:\n",
    "            outShape[new_height, new_width] = input_shape[height,width] / Stride (结果向上取整)\n",
    "            \n",
    "            pad_need_total = (outShape – 1)  × Stride + filter - input_shape\n",
    "            \n",
    "            [pad_top, pad_left] = pad_need_total / 2 (结果取整)\n",
    "            \n",
    "            [pad_down, pad_right] = pad_need_total - [pad_top, pad_left]\n",
    "    \"\"\"\n",
    "    # 输入数据的shape=[batch, height, width, channels(图像通道数)]\n",
    "    input_shape = input.shape[1:3]\n",
    "    # 卷积核的shape=[height, width, in_channels(图像通道数), out_channels(卷积核/特征图数量)]\n",
    "    filter_shape = filter.shape[0:2]\n",
    "    # 浮点型转整型\n",
    "    outShape = outShape.astype(np.uint8)    \n",
    "    \n",
    "    # 总共需要pad的行列数\n",
    "    pad_need_total = (np.array(outShape) - np.array([1,1])) * stride \\\n",
    "                        + np.array(filter_shape) - np.array(input_shape) \n",
    "    # 左侧和上方需要pad的列和行数量\n",
    "    pad_TopAndLeft = (pad_need_total / 2).astype(np.uint8)\n",
    "    # 右侧和下方需要pad的列和行数量\n",
    "    pad_DownAndRight = pad_need_total - pad_TopAndLeft    \n",
    "    \n",
    "    #print('top:%s\\ndown:%s'%(pad_TopAndLeft[0], pad_DownAndRight[0]))\n",
    "    #print('letf:%s\\nright:%s'%(pad_TopAndLeft[1],pad_DownAndRight[1]))\n",
    "    \n",
    "    inp_tmp = np.pad(input, \\\n",
    "    ((0, 0), (pad_TopAndLeft[0], pad_DownAndRight[0]), \\\n",
    "     (pad_TopAndLeft[1], pad_DownAndRight[1]), (0, 0)), 'constant', constant_values=0)\n",
    "    \n",
    "    return inp_tmp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 每个卷积核运算一次的计算过程\n",
    "def perCon2d(input, filter, output, stride, out_channels):\n",
    "    # 卷积核的shape=[height, width, in_channels(图像通道数), out_channels(卷积核/特征图数量)]\n",
    "    f_s = filter.shape\n",
    "    # 每次移动卷积核后,卷积核纵坐标起始位置\n",
    "    next_height_start_location = -stride\n",
    "    # 卷积核纵向移动次数\n",
    "    for height in range(output.shape[1]):\n",
    "        # 从新计算纵坐标起始位置\n",
    "        next_height_start_location += stride\n",
    "        # 每次移动卷积核后,卷积核横坐标起始位置\n",
    "        next_width_start_location = 0                \n",
    "        # 卷积核横向移动次数\n",
    "        for width in range(output.shape[2]):\n",
    "            # 各深度卷积总和\n",
    "            along_depth_sum = 0\n",
    "            for depth in range(3):\n",
    "                # 三个维度卷积相加\n",
    "                depth_result = \\\n",
    "                    (input[0, next_height_start_location:next_height_start_location+f_s[0], \\\n",
    "                            next_width_start_location:next_width_start_location+f_s[1], depth] * \\\n",
    "                        filter[:, :, depth, out_channels]).sum()\n",
    "                along_depth_sum += depth_result\n",
    "            # 从新计算横坐标起始位置\n",
    "            next_width_start_location += stride\n",
    "            output[0][height][width][out_channels] = along_depth_sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 自定义卷积函数实现卷积前向传播\n",
    "def conv2d(input, filter, stride, padding):\n",
    "    # 输入数据的shape=[batch, height, width, channels(图像通道数)]\n",
    "    in_s = input.shape\n",
    "    # 卷积核的shape=[height, width, in_channels(图像通道数), out_channels(卷积核/特征图数量)]\n",
    "    f_s = filter.shape\n",
    "    \n",
    "    # 参数格式检测,不符合则提示并终止程序\n",
    "    assert len(in_s) == 4, 'input size rank 4 required!'\n",
    "    assert len(f_s) == 4, 'filter size rank 4 required!'\n",
    "    assert f_s[2] == in_s[3], 'intput channels not match filter channels!'\n",
    "    assert f_s[0] >= stride and f_s[1] >= stride, 'filter should not be less than stride!'\n",
    "    assert padding in ['SAME', 'VALID'], 'padding value[{0}] not allowded!'.format(padding)\n",
    "    \n",
    "    # padding='SAME',则向上取整ceil(输出图像宽高=输入图像宽高/步长)\n",
    "    if padding != 'VALID':\n",
    "        # 当前out_shape=[height, width]\n",
    "        out_shape = np.ceil(np.array(in_s[1: 3])/stride) \n",
    "        # 图像补0处理\n",
    "        input = picPad0(input, filter, stride, out_shape)\n",
    "    else:\n",
    "        # padding='VALID',则floor(输出图像宽高=(输入图像宽高-卷积核宽高)/步长+1)\n",
    "        out_shape = (np.array(in_s[1: 3]) - np.array(f_s[:2]))/stride + 1\n",
    "    \n",
    "    # 定义输出矩阵的shape\n",
    "    out_shape = np.concatenate([in_s[:1], out_shape, f_s[-1:]])\n",
    "    # 初始化out_shape型的全0矩阵\n",
    "    output = np.zeros(out_shape.astype(np.uint8))    \n",
    "    \n",
    "    \"\"\"\n",
    "        卷积计算开始\n",
    "    \"\"\"\n",
    "    for out_channels in range(output.shape[3]):\n",
    "        #每个卷积核计算一次\n",
    "        perCon2d(input, filter, output, stride, out_channels)\n",
    "\n",
    "    return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 先定义个计算图用于运行tf\n",
    "input_tensor = tf.placeholder(\n",
    "    tf.float32, shape=[None, None, None, None], name='input')\n",
    "filter_tensor = tf.placeholder(\n",
    "    tf.float32, shape=[None, None, None, None], name='filter')\n",
    "\n",
    "output_tensor1 = tf.nn.conv2d(\n",
    "    input_tensor, filter_tensor, padding='SAME', strides=[1, 2, 2, 1])\n",
    "\n",
    "output_tensor2 = tf.nn.conv2d(\n",
    "    input_tensor, filter_tensor, padding='VALID', strides=[1, 3, 3, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 测试自定义函数\n",
    "def testCon2d(img, padding):\n",
    "    \"\"\"\n",
    "        padding有两种: SAME 和 VALID\n",
    "    \"\"\"\n",
    "    \n",
    "    # 评估分数初始化为\n",
    "    final_score = 0\n",
    "    \n",
    "    # 调用tensorflow函数库的con2d\n",
    "    if padding == 'SAME':\n",
    "        # 随机生成的卷积核\n",
    "        filter = np.random.uniform(size=[5, 5, 3, 8])    \n",
    "        # 调用自定义函数con2d\n",
    "        output = conv2d(img, filter, 2, padding)\n",
    "        # 调用tensorflow函数库的con2d\n",
    "        with tf.Session() as sess:\n",
    "            output_tf = sess.run(\n",
    "                output_tensor1,\n",
    "                feed_dict={\n",
    "                    input_tensor: img,\n",
    "                    filter_tensor: filter\n",
    "                })\n",
    "    else:\n",
    "        # 随机生成的卷积核\n",
    "        filter = np.random.uniform(size=[5, 5, 3, 8])\n",
    "        # 调用自定义函数con2d\n",
    "        output = conv2d(img, filter, 3, padding)\n",
    "        # 调用tensorflow函数库的con2d\n",
    "        with tf.Session() as sess:\n",
    "            output_tf = sess.run(\n",
    "                output_tensor2,\n",
    "                feed_dict={\n",
    "                    input_tensor: img,\n",
    "                    filter_tensor: filter\n",
    "                })\n",
    "    \n",
    "    # 输出矩阵shape检测\n",
    "    assert output.shape == output_tf.shape, '[padding] shape mismatch [{}] vs [{}]'.format(\n",
    "        output.shape, output_tf.shape)    \n",
    "    # shape算对了得20分\n",
    "    final_score += 20\n",
    "    \n",
    "    # 自定义函数与tf库函数进行结果比较\n",
    "    diff = np.mean(np.abs(output - output_tf))\n",
    "    \n",
    "    # 如果这一行没有报错的话,那么实现可以认为是正确(误差范围)\n",
    "    assert diff < 1e-5, '[{}] value mismatch [{}]'.format(padding, diff)\n",
    "    # 数值算对了得30分\n",
    "    final_score += 30\n",
    "    \n",
    "    print('test padding = [{}] passed...'.format(padding))\n",
    "    \n",
    "    return final_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test padding = [SAME] passed...\n",
      "test padding = [VALID] passed...\n",
      "Your final score:[100]\n"
     ]
    }
   ],
   "source": [
    "# 自定义conv2d检测验证\n",
    "try:\n",
    "    \n",
    "    same_score = testCon2d(img, 'SAME')\n",
    "    valid_score = testCon2d(img, 'VALID')\n",
    "        \n",
    "except Exception as ex:\n",
    "    print(ex)\n",
    "\n",
    "print('Your final score:[{}]'.format(same_score + valid_score))"
   ]
  }
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